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Water confined within nanochannels with specific functionalities serves as the foundation for a variety of emerging nanofluidic applications. However, the structure and dynamics of the confined liquid are susceptibly influenced by practically hard-to-avoid defects, yet knowledge of this fact remains largely unexplored. Here, using extensive molecular dynamics simulations, we elucidate the significant influence of geometric and charge defects on one-dimensional confined water. We show that the two types of defects can both reshape the water density distribution by constraining the translocation of water molecules along the circumferential direction. In addition to structural alterations, collective translocation and rotation of water slabs arise during transportation under external pressure. Below the temperature threshold marking the initiation of liquid-solid transition, the geometric defect retards water diffusion through a pinning effect, while the charge defect induces an anti-freezing effect. The latter is attributed to the electrostatic interaction between the charge defect and water molecules that hinders the formation of a stable hydrogen bond network by disrupting molecular dipole orientation. Consequently, this behavior results in a reduction in the number and lifetime of hydrogen bonds within the phase transition interval. The distinct roles of the two types of defects could be utilized to control the structure and dynamics of confined liquids that may result in distinct functionalities for nanofluidic applications. [ABSTRACT FROM AUTHOR]

We have applied path-integral molecular dynamics simulations to investigate the impact of nuclear quantum effects on the vibrational dynamics of water molecules at the water–air interface. The instantaneous fluctuations in the frequencies of the O–H stretch modes are calculated using the wavelet method of time series analysis, while the time scales of vibrational spectral diffusion are determined from frequency-time correlation functions and joint probability distributions. We find that the inclusion of nuclear quantum effects leads not only to a redshift in the vibrational frequency distribution by about 120 cm−1 for both the bulk and interfacial water molecules but also to an acceleration of the vibrational dynamics at the water–air interface by as much as 35%. In addition, a blueshift of about 45 cm−1 is seen in the vibrational frequency distribution of interfacial water molecules compared to that of the bulk. Furthermore, the dynamics of water molecules beyond the topmost molecular layer was found to be rather similar to that of bulk water. [ABSTRACT FROM AUTHOR]

The hydrophilic pore morphology and solvent diffusion within model (amphiphilic) polymer membranes are simulated by dissipative particle dynamics (DPD). The polymers are composed of a backbone of 18 covalently bonded A beads to which at regular intervals side chains are attached. The side chains are composed of linear Ap chains (i.e., –A1–A2...Ap) from which two branches, [AsC] and [ArC], split off (s ≤ r). C beads serve as functionalized hydrophilic pendent sites. The branch lengths (s + 1 and r + 1) are varied. Five repeat unit designs (with general formula A3[Ap[AsC][ArC]]) are considered: A2[A3C][A3C] (symmetric branching), A2[A2C][A4C], A2[AC][A5C], A2[C][A6C] (highly asymmetric branching), and A4[AC][A3C]. The distribution of water (W) and W diffusion through nanophase segregated hydrophilic pores is studied. For similar primary length p, an increase in side chain symmetry favors hydrophilic pore connectivity and long-range water transport. C beads located on the longer [ArC] branches reveal the highest C bead mobility and are more strongly associated with water than the C beads on the shorter [AsC] branches. The connectivity of hydrophilic (W and W + C) phases through mapped replica of selected snapshots obtained from Monte Carlo tracer diffusion simulations is in line with trends found from the W bead diffusivities during DPD simulations. The diffusive pathways for protons (H+) in proton exchange membranes and for hydronium (OH−) in anion exchange membranes are the same as for solvents. Therefore, control of the side chain architecture is an interesting design parameter for optimizing membrane conductivities. [ABSTRACT FROM AUTHOR]

In water-guided laser technology, the stability of water jets is crucial to ensure the efficient transmission of laser energy. However, the thermal effects generated when high-power lasers are coupled with water jets are bound to impact the stability of the water jets, thus becoming a critical issue that restricts the development of high-power water-guided laser technology. In addressing this issue, this paper establishes a temperature model for coupling high-power lasers with water jets. Subsequently, with validation of the model's effectiveness through experimental data, simulations are conducted to analyze the temperature distribution within the water jet. During the simulation process, lasers with different parameters were coupled with water jets to analyze the temperature variation law of the water jets. Additionally, the maximum laser power coupled with water jets of different lengths was solved. Based on the calculated temperature values of the water jet, simulate the evolution of its profile over time when it has an initial temperature gradient. Simultaneously, perform a three-dimensional reconstruction of the obtained perturbed profile and conduct ray tracing to analyze the laser's transmission losses within the perturbed profile. Finally, high-speed cameras are utilized to capture the profile of the water jet, validating the laser-induced fragmentation behavior in the water jet. The research findings will provide a significant reference value for selecting laser parameters and controlling thermal effects in water-guided high-power technology. [ABSTRACT FROM AUTHOR]

Electrochemical water splitting is crucial for the decarbonization of industrial processes and the coupling of renewable energy sources. Evaluation of individual HER and OER contributions to the transfer process is essential for optimizing electrolysis system performance. This study uses nickel-cobalt layered double hydroxide (NiCo-LDH) as a solid-state redox mediator (SRM), achieving efficient H 2 and O 2 separation. This study provides an in-depth analysis of kinetic and ion/charge/mass transfer mechanisms linked to various characteristic impedances in alkaline decoupled water electrolysis (DWE) system by integrating Electrochemical Impedance Spectroscopy (EIS) and Distribution of Relaxation Times (DRT) methods. The characteristic frequency evolution is consistent with the charge-discharge state of SRM and mass transfer frequency is related to the bubble size and gas diffusion rate of electrocatalysts at different current densities. The charge transfer R ct dominates the total polarization impedance in decoupled HER, and mass transfer R m decreases remarkably in decoupled OER. OER shows lower R ct with Fe species existence and lower total polarization impedance than HER. R m in decoupled HER increases by 38.24% and OER by 29.82% during prolonged decoupled test. This study provides valuable insights into the impedance contributions and kinetic mechanisms through novel electrolysis approaches, guiding further optimization of decoupled electrolyzer and electrode. [Display omitted] • High mass loading NiCo-LDH showed excellent decoupling performance. • The DRT method identified different electrochemical processes in DWE. • Kinetic and transfer analysis of electrode contributions in DWE system. • Explain the reasons for the impedance variation during the long-term DWE test. • Achieve continuous and stable HER/OER decoupling at high current densities. [ABSTRACT FROM AUTHOR]

The pressure sensor placement in the water distribution networks (WDNs) is a typical NP‐Hard problem. The goal is to monitor the running state of the whole network area by placing a small number of pressure sensors. This letter proposes an enhanced Rafflesia optimization algorithm (EROA) to solve this problem. The simulation results show that compared with the original ROA algorithm and the traditional intelligent optimization algorithms, the proposed EROA algorithm exhibits superior optimization capabilities and solution efficiency, and can provide a more reasonable sensor placement scheme. [ABSTRACT FROM AUTHOR]

Stratospheric transit time distributions (age‐of‐air spectra) are estimated using time series of satellite water vapor (H2O) measurements from the Microwave Limb Sounder over 2004 to 2021 assuming stationary transport. Latitude‐altitude dependent spectra are derived from correlations of interannual H2O anomalies with respect to the tropical tropopause source region, fitted with an inverse Gaussian distribution function. The reconstructions accurately capture interannual H2O variability in the "tropical pipe" and near‐global lower stratosphere, regions of relatively fast transport (∼1–2 years) in the Brewer‐Dobson circulation. The calculations provide novel observational estimates of the corresponding "short transit‐time" part of the age spectrum in these regions, including the mode. However, the H2O results do not constrain the longer transit‐time "tail" of the age spectra, and the mean age of air and spectral widths are systematically underestimated compared to other data. We compare observational results with parallel calculations applied to the WACCM chemistry‐climate model and the CLaMS chemistry‐transport model, and additionally evaluate the method in CLaMS by comparing with spectra from idealized pulse tracers. Because the age spectra accurately capture H2O interannual variations originating from the tropical tropopause, they can be used to identify "other" sources of variability in the lower stratosphere, and we use these calculations to quantify H2O anomalies in the Southern Hemisphere linked to the Australian New Years fires in early 2020 and the Hunga volcanic eruption in 2022. Plain Language Summary: Stratospheric water vapor (H2O) is mainly controlled by transport across the cold tropical tropopause, which sets the entry value for the global stratosphere. Interannual variations in H2O originate near the tropical tropopause and then propagate throughout the stratosphere with the global Brewer‐Dobson circulation (BDC), where anomalies are lagged in time and smoothed by mixing. We use the observed time series of H2O from the Microwave Limb Sounder during 2004–2021 to calculate transit time distributions (also called age spectra) from the tropical tropopause source region. The results capture H2O variability in the tropics up to 30 km and in the global lower stratosphere, regions of relatively fast transport (∼1–2 years) in the BDC. The calculations provide novel observational estimates of the age spectra in these regions. The calculations are straightforward to apply to global models, and we compare observational results with simulations from the WACCM and CLaMS models. Key Points: Stratospheric transit time distributions (age spectra) are derived from time series of satellite water vapor measurementsWater vapor reconstructions from age spectra capture detailed variability in the tropics up to 30 km and in the global lower stratosphereAge spectrum results are compared between observations and global model simulations [ABSTRACT FROM AUTHOR]

Designing effective electrode material is crucial for developing ultra‐long lifetime batteries, thereby reducing daily battery costs. Current electrode materials are typically solid or liquid state, with an intermediate colloidal state offering the advantages of fixed redox‐active species, akin to solid‐state materials, and the absence of rigid atomic structure, akin to liquid‐state materials, while avoiding the particle pulverization and uncontrolled migration. Herein, an aqueous Zn||Pluronic F127 (PF127)/ZnI2 colloid battery is developed utilizing the inherent water molecular control effect of ZnSO4. In this system, ZnSO4 in the electrolyte acts as a water molecular valve, regulating the water content within the PF127 polymer to form a PF127 colloid. The resulting aqueous Zn||PF127/ZnI2 colloid battery exhibits an ultra‐long cycling lifetime and compatibility with various simulated and practical operating conditions, highlighting its potential for practical applications. Additionally, this battery design concept offers a platform for constructing ultra‐stable aqueous batteries. [ABSTRACT FROM AUTHOR]

As the urban population increases, the consumption of water resources is also increasing. Safely and effectively supplying water to cities has become an issue that urgently needs to be addressed. The purpose of this research is to substantially reduce the number of contaminants in water distribution networks (WDNs) by using valve control, ensuring that the water infrastructure is not impacted by the adverse effects of wastewater. In addition, an improved parallel binary gannet algorithm (IPBGOA) is proposed and combined with this approach to solve the optimization problem of WDN contamination efficiently. The proposed method is compared with the gannet optimization algorithm (GOA), particle swarm optimization (PSO), differential evolution (DE), the grey wolf optimization (GWO), and the genetic algorithm (GA) on synthetic benchmark networks in simulation experiments. The evidence from the study indicates that the algorithm proposed in this paper is significantly more efficient and reliable than the comparison methods. [ABSTRACT FROM AUTHOR]

Practical Application The aim of this study was to investigate the effect of different ultrasound treatment (UT) conditions (Control, UT‐150, UT‐300, UT‐450, Vacuum‐UT‐150, Vacuum‐UT‐300, Vacuum‐UT‐450) on the brining kinetics and meat quality of chicken breast. The results showed that vacuum‐ultrasonic‐assisted treatment greatly accelerated the transfer of moisture and NaCl, and the highest yield was obtained by ultrasonic power of 450 W. The mass transfer kinetics (k1 and k2) were significantly related to vacuum pretreatment and ultrasonic power. The values of k1 for total and moisture weight changes decreased with the increase of ultrasonic power, whereas the values of k2 increased with vacuum pretreatment. The application of ultrasound treatment with vacuum improved the NaCl effective diffusion coefficients (De) from 1.189 × 10−9 to 1.308–1.449 × 10−9 m2/s, and the highest De was found with Vacuum‐UT‐450. The treatment of ultrasound and vacuum can reduce shear force and enhance the water‐holding capacity (WHC). According to the analysis of water distribution, vacuum and ultrasound could decrease the T23 values, indicating that the mobility of water decreased. The result of microscopic observation further supported that the disruption of myofibrils was related to the tenderness and WHC changes, which was caused by vacuum and ultrasound treatment. Thus, Vacuum‐UT brining could be employed as an emerging technology for improving the efficiency of brining and meat quality of other meat.Vacuum‐ultrasonic‐assisted static brine is an effective and feasible treatment to replace tumbling treatment for maintaining the integrity of the muscle bundles and accelerating the brining rate. [ABSTRACT FROM AUTHOR]

ABSTRACT It has been broadly reported that future climate change will most likely affect the spatio‐temporal distribution of water resources and consequently droughts. There is a prevailing notion that an increase in temperature and frequency of heat waves are expected to result in more intense droughts in the coming years. In this study, we aimed to evaluate the effect of the potential evapotranspiration (PET) method selection on future drought projections over Poland. In our study, simulations of the Soil and Water Assessment Tool (SWAT) model were conducted, utilising an ensemble of six EURO‐CORDEX projections, spanning the period from 2006 to 2100 under the RCP8.5 scenario. Two model setups with two different PET methods (Penman‐Monteith—PM and Hargreaves—HAR) were used. For drought conditions evaluation we selected the Standardized Precipitation Index (SPI) and Standardized Precipitation‐Evapotranspiration Index (SPEI) for meteorological drought, Standardized Streamflow Index (SSI) for hydrological drought, and Standardized Soil Moisture Index (SMI) for agricultural drought. The meteorological and hydrological droughts were calculated using a 12‐month time aggregation window, while agricultural drought was calculated using a 3‐month window. Climate projections revealed that by 2080s annual mean temperature and precipitation increase is expected by up to +3.4°C and +10.3% respectively. Under future climate conditions duration and severity of meteorological droughts are projected to decrease. PM method leads to a higher PET increases (1.35 mm year−1) than the HAR method (1.1 mm year−1) throughout the century which entail diverging signal of change for agricultural and hydrological droughts. PM‐ and HAR‐based simulations indicate increase in the total duration and cumulative severity of agricultural droughts, buthowever, for HAR‐based projections, the increase is much less. For hydrological droughts the signal of change is similar for both PET methods, but considerably distinct in magnitude. Considering the entire simulation period, by the end of the century cumulative severity of hydrological droughts is projected to decrease, with a much more pronounced decline for HAR (70% reduction) than for the PM method (35% reduction). Our study demonstrated that methodological choices are crucial to the assessment of future drought risk under climate change. [ABSTRACT FROM AUTHOR]

Low organic matter content is one of the main constraints in arid and semiarid regions. This constraint and its negative influences on soils and plant growth may be alleviated by biochar (BC). Furthermore, improving soil physical and hydraulic attributes by application of biochar has received increased attention. Therefore, in the present study, the effects of sugarcane bagasse-derived biochar on the structural stability, water availability, and pore-size distribution (PSD) of three texturally different calcareous soils collected from different agro-climatologically regions were examined during a long-term experiment. Low and high-temperature biochars, produced in a muffle furnace by the traditional slow pyrolysis method at 300 °C (BC300) and 600 °C (BC600) were evaluated. Pots (15 kg) were filled with three different silty-clay Inceptisols (SCInc), silty-clay-loam Alfisols (SCLAlf), and loam Aridisols (LArid) soils mixed with 0 (control), 1, 2, and 3 w/w% of BC300 and BC600 during 540 days of incubation. The high energy moisture characteristic (HEMC) data was modeled using a modified van Genuchten function to quantify aggregate stability through stability ratio (SR) and structural stability index (SSI). The plant available water (PAW), least limiting water range (LLWR), and integral water capacity (IWC) were calculated with two matric suctions (h) of 330 cm for field capacity (FC) and 15,000 cm for permanent wilting point (PWP). Then the integral energy (EI) values were calculated (EIIWC). Results indicated that the incorporation of 3 w/w% biochar significantly (p < 0.01) increased SR (35 to 100%) and SSI (21 to 28%) indices in all three soils. Biochar significantly increased modal suction (MS) in LArid soils (5 to 158%); whereas, decreased MS of the other soils (3 to 43%). MS, SR, and SSI of BC300 and BC600-treated soils were not significantly different. PAW, LLWR, and IWC significantly decreased in the SCInc (18 to 61%, 8 to 44%, and 6 to 35%) and SCLAlf (8 to 44%, 18 to 35%, and 20 to 47%) soils and increased in LArid (4 to 54%, 3 to 61%, and 24 to 111%) soil with increasing biochar doses. There were no changes in EIIWC in biochar-treated LArid soil where PAW, LLWR, and IWC increased. Biochar increased EIIWC across the studied soil from 1% to 3.38 folds, thereby increasing the gradient of water potential to absorb the available water. Soil and soil-biochar mixtures exhibited heterogeneous and multimodal pore-size distribution (PSD). Biochar promoted the PSD peaks related to water-transmitting pores in SCInc and SCLAlf soils while decreased in LArid soil. In conclusion, results indicated that among the applied levels of biochar, the application of 3 w/w% biochar is suggested as a suitable way to improve soil physical behavior and structural stability. [ABSTRACT FROM AUTHOR]

In this work, a steady-state, three-dimensional and non-isothermal numerical model for a proton exchange membrane electrolysis cell (PEMEC) is established. Based on this model, the distribution of catalyst loading is specifically designed according to the flow characteristics of both parallel and serpentine channels. In general, the catalyst loading is progressively reduced from inlet to outlet along the flow direction to match the local water content, leading to an innovative segmented catalyst layer which has not been studied yet for PEMEC applications. The electrochemical behavior of different segmentation schemes is investigated by comparing their polarization curves normalized by either electrode area or catalyst loading, while other physical fields such as velocity, pressure, water mole fraction and temperature distributions are also characterized. The numerical results reveal that a reasonable distribution of catalyst can reduce its amount of usage while still maintaining most of the PEMEC performance. In other words, the cost performance is significantly improved. This is mainly attributed to the full use of uneven water distribution in the flow channel, which improves the catalyst utilization efficiency significantly. This strategy is proved to be effective for both serpentine and parallel channels, ensuring a broad application prospect. • A novel catalyst layer segmentation strategy is proposed for PEM electrolyzer. • The catalyst loading is distributed according to the local water content. • Specific current normalized by catalyst weight is improved due to loading reduction. • Physical field distribution inside the PEM electrolyzer is not changed too much. • Cost performance of the PEM electrolyzer is improved significantly. [ABSTRACT FROM AUTHOR]

Since the inception of the Industrial 4.0 revolution, industrial cyber‐physical systems (CPSs) have become integral to critical infrastructures and industrial sectors, including water treatment and distribution systems. Integrating physical and digital worlds has made communication systems within these plants—comprising actuators, sensors, and controllers—vulnerable to advanced cyber‐attacks. Safeguarding the nation's critical infrastructure has thus attracted significant interest from both academia and industry. This article thoroughly examines water treatment and distribution CPSs, detailing their architectural design, devices, applications, and security standards. It analyzes various cyber‐attacks and explores CPS security vulnerabilities and their detection and mitigation techniques. Additionally, it reviews the trends in machine learning (ML) and deep learning (DL) intrusion detection system (IDS) solutions, highlighting their advantages and disadvantages. The article evaluates current datasets and testbeds, identifying some of the best‐performing IDS algorithms tested on each dataset compared to previous research, which could serve as benchmarks in this field. Finally, it proposes data augmentation techniques to generate comprehensive datasets, identifies research gaps, and suggests potential improvements to enhance IDS performance. [ABSTRACT FROM AUTHOR]

Detecting faulty pipelines in water management systems is crucial for ensuring a reliable supply of clean water. Traditional inspection methods are often time-consuming, costly, and prone to errors. This study introduces an AI-based model utilizing images to detect pipeline defects, focusing on leaks, cracks, and corrosion. The YOLOv8 model is employed for object detection due to its exceptional performance in detecting objects, segmentation, pose estimation, tracking, and classification. By training on a large dataset of labeled images, the model effectively learns to identify visual patterns associated with pipeline faults. Experiments conducted on a real-world dataset demonstrate that the AI-based model significantly outperforms traditional methods in detection accuracy. The model also exhibits robustness to various environmental conditions such as lighting changes, camera angles, and occlusions, ensuring reliable performance in diverse scenarios. The efficient processing time of the model enables real-time fault detection in large-scale water distribution networks implementing this AI-based model offers numerous advantages for water management systems. It reduces dependence on manual inspections, thereby saving costs and enhancing operational efficiency. Additionally, the model facilitates proactive maintenance through the early detection of faults, preventing water loss, contamination, and infrastructure damage. The results from the three conducted experiments indicate that the model from Experiment 1 achieves a commendable mAP50 of 90% in detecting faulty pipes, with an overall mAP50 of 74.7%. In contrast, the model from Experiment 3 exhibits superior overall performance, achieving a mAP50 of 76.1%. This research presents a promising approach to improving the reliability and sustainability of water management systems through AI-based fault detection using image analysis. [ABSTRACT FROM AUTHOR]

The proton exchange membrane fuel cell (PEMFC), with a high energy conversion efficiency, has become an important means of hydrogen energy utilization. However, water condensation is unavoidable in the PEMFC because of low operating temperatures. The impact of liquid water on PEMFC performance and stability is significant. The gas diffusion layer (GDL) provides a critical transport path for liquid water in the PEMFC. Liquid water saturation and distribution in the GDL determine water flooding and mass transfer efficiency in the PEMFC. In this study, focusing on the effects of the water introduction method, osmotic pressure, and contact angle, the liquid water transport in the GDL was numerically investigated based on a pore-scale model using the volume of fluid (VOF) method. The results showed that compared with the conventional water introduction method without cracks, the saturation and spatial distribution of water inside the GDL obtained in the simulation were more consistent with the experimental results when the water was introduced through the microporous layer (MPL) crack. It was found that increasing the osmotic pressure resulted in a faster rate of water penetration, faster approaching the steady-state performance, and higher saturation. The ultra-high osmotic pressure contributed to the secondary breakthrough with a significant increase in saturation. Increasing the contact angle caused higher capillary resistance, especially in the region with small pore sizes. At a constant osmotic pressure, as the contact angle increased, the liquid water gradually failed to penetrate into the small pores around the transport path, causing saturation reduction and an ultimate failure to break through the GDL. Increasing the contact angle contributed to a higher breakthrough pressure and secondary breakthrough pressure. [ABSTRACT FROM AUTHOR]

Surface water fraction mapping is an essential preprocessing step for the subpixel mapping (SPM) of surface water, providing valuable prior knowledge about surface water distribution at the subpixel level. In recent years, spectral mixture analysis (SMA) has been extensively applied to estimate surface water fractions in multispectral images by decomposing each mixed pixel into endmembers and their corresponding fractions using linear or nonlinear spectral mixture models. However, challenges emerge when introducing existing surface water fraction mapping methods to hyperspectral images (HSIs) due to insufficient exploration of spectral information. Additionally, inaccurate extraction of endmembers can result in unsatisfactory water fraction estimations. To address these issues, this paper proposes an adaptive unmixing method based on iterative multi-objective optimization for surface water fraction mapping (IMOSWFM) using Zhuhai-1 HSIs. In IMOSWFM, a modified normalized difference water fraction index (MNDWFI) was developed to fully exploit the spectral information. Furthermore, an iterative unmixing framework was adopted to dynamically extract high-quality endmembers and estimate their corresponding water fractions. Experimental results on the Zhuhai-1 HSIs from three test sites around Nanyi Lake indicate that water fraction maps obtained by IMOSWFM are closest to the reference maps compared with the other three SMA-based surface water fraction estimation methods, with the highest overall accuracy (OA) of 91.74%, 93.12%, and 89.73% in terms of pure water extraction and the lowest root-mean-square errors (RMSE) of 0.2506, 0.2403, and 0.2265 in terms of water fraction estimation. This research provides a reference for adapting existing surface water fraction mapping methods to HSIs. [ABSTRACT FROM AUTHOR]

Due to the detrimental effects of moisture in the built environment, there is a continuous interest in non-destructive experimental techniques that quantify and/or localise moisture in materials. Most existing experimental techniques, however, typically focus on macroscopic moisture contents in samples rather than the microscopic distribution of water in the individual pores of building materials. For the latter, a popular method such as X-ray computed tomography is not readily applicable, due to the gap between its spatial resolution limit and the typical pore sizes of building materials. Nuclear magnetic resonance (NMR) relaxometry is capable of measuring water in pores of both the nanometer and micrometer scale and is therefore an interesting possibility. While most NMR research focusses on water-saturated materials or overall moisture contents, this study determines the size distributions of the water islands in unsaturated materials with NMR, and compares results to X-ray computed tomography (XCT) images and pore network model (PNM) simulations. Results on unsaturated materials show that NMR focusses on the biggest water islands (i.e. in capillary filled pores) and disregards the hydrogen nuclei in smaller water islands (i.e. stored in pore corners). NMR relaxometry is therefore only adept at providing very rough estimates of the size of water-filled pores, especially since post-processing of the NMR experiments to obtain these water island size distributions involves a lot of uncertainty. [ABSTRACT FROM AUTHOR]

Environmental DNA (eDNA) has revolutionized ecological research, particularly for biodiversity assessment in various environments, most notably aquatic media. Environmental DNA analysis allows for non‐invasive and rapid species detection across multiple taxonomic groups within a single sample, making it especially useful for identifying rare or invasive species. Due to dynamic hydrological processes, eDNA samples from running waters may represent biodiversity from broad contributing areas, which is convenient from a biomonitoring perspective but also challenging, as hydrological knowledge is required for meaningful biological interpretation. Hydrologists could also benefit from eDNA to address unsolved questions, particularly concerning water movement through catchments. While naturally occurring abiotic tracers have advanced our understanding of water age distribution in catchments, for example, current geochemical tracers cannot fully elucidate the timing and flow paths of water through landscapes. Conversely, biological tracers, owing to their immense diversity and interactions with the environment, could offer more detailed information on the sources and flow paths of water to the stream. The informational capacity of eDNA as a tracer, however, is determined by the ability to interpret the complex biological heterogeneity at a study site, which arguably requires both biological and hydrological expertise. As eDNA data has become increasingly available as part of biomonitoring campaigns, we argue that accompanying eDNA surveys with hydrological observations could enhance our understanding of both biological and hydrological processes; we identify opportunities, challenges, and needs for further interdisciplinary collaboration; and we highlight eDNA's potential as a bridge between hydrology and biology, which could foster both domains. This article is categorized under:Science of Water > Hydrological ProcessesScience of Water > MethodsWater and Life > Nature of Freshwater Ecosystems [ABSTRACT FROM AUTHOR]

This paper presents a novel method of treating high water content dredged slurry by vacuum pre-pressure using woven rice straw as horizontal drainage boards (SHDs). This not only helps to avoid the impact of plastic drainage boards on the environment, but also helps to utilize agricultural related waste. The study aimed to investigate the effect of SHDs degradation on the vacuum transfer within the horizontal drainage boards and the consolidation characteristics of dredged slurry. Indoor vacuum preloading model tests were conducted to investigate soil settlement, straw degradation, vacuum variation and water content distribution within the drainage board. The results show that SHDs can significantly improve the consolidation of dredged slurry. The closer the straw is to the interface between the drainage board and the vacuum pipe, the greater the degree of degradation. The water content was distributed with depth in an oblique "z" shape, while a point with higher water content existed at 1/3 of the soil above the drainage boards. In addition, the low water content zone around the drainage board shows an elliptical shape due to the influence of gravity. These research results have some reference value for the ecological treatment of dredged slurry and straw. [ABSTRACT FROM AUTHOR]

Flow efficiency in a two‐strand continuous casting tundish is studied by analyzing the residential time distribution (RTD) curves in a small‐scale tundish water model using a conductive NaCl solution tracer. The velocity fields in the tundish water model are measured by particle image velocimetry, which is used to validate the results of the mathematical model in the article. It is found that the tracer concentration has a significant impact on the predicted dead volume fraction in the RTD analysis. Validated mathematical modeling of the computational fluid dynamics (CFD) technology is performed to explore the root cause of the defective results in the RTD analysis. It is found that the flow inside the tundish is sensitive to density variations caused by the injected tracer. A denser tracer will stay lower in the tundish by gravity and flow out of the tundish more quickly. A proper tracer concentration in the water model experiments is discussed to visualize the dead volume and improve tundish furniture design efficiently for future work, a new method using CFD modeling is proposed in this article, which can directly demonstrate the dead volume's location. [ABSTRACT FROM AUTHOR]

This study investigated the prospective effect of ApnA enzyme under different concentrations (µL/100 mL soymilk) compared to chemical (pH, MgCl2, and K-carrageenan, respectively) as tofu coagulants. The resultant tofu samples were analyzed for compositional analysis, thermal properties, water distribution, and microstructure properties. The higher concentration of enzyme used, the higher resulted moisture content of tofu. ApnA enzyme increased the cross-linking through protein molecules and trapped more water within the gel network. Tofu samples prepared by different concentrations of ApnA enzyme displayed significantly less freezable water content (15.44, 12.84, and 19.46 g/100 g). In particular, 800 µL ApnA/100 mL soymilk formed an interconnected gel matrix with regular distribution with almost invisible cavities. The thermal pretreatment and the increased coagulation time might encourage this irregular structure. On the other hand, the gel network coagulated using the reduction of pH showed a weaker gel due to an accelerated acidification. [ABSTRACT FROM AUTHOR]

Timely pipe break and burst detection and localization are important for proactive management of water distribution systems (WDSs). This paper presents a novel timing-based method for fast localization of hydraulic transient waves that may occur from a pipe break or burst event. The proposed technique deals with the arrival time difference from sensor pairs coupled with a new graph-based transient wave propagation mapping strategy to identify potential link (pipe) candidates for the transient event. The fusion of the wave arrival differences from all combinations of sensor pairs in the network is then used to more comprehensively locate the transient event source among the candidates. This novel integration of topological information avoids missing the correct candidate by identifying all possible solutions, and thus improves the reliability of the localization. Applications to numerical case studies and laboratory experiments show that the method can accurately locate the transient source even with uncertainties from measurement devices and address issues with previous conventional methods concerning detection reliability. [ABSTRACT FROM AUTHOR]

As urbanization has accelerated, the coverage area of water distribution networks (WDNs) has been significantly increasing, making the management of large WDNs more difficult. To manage WDNs more accurately, water utilities split them into district metered areas (DMAs) of different sizes. However, the design of static DMAs has limitations in hydraulic performance during abnormal conditions in a WDN. To address this issue, first, this paper proposes a method for optimal DMA layout based on the combination of the self-organizing map (SOM) algorithm and the Leiden algorithm, achieving the optimal multilevel DMA layout and obtaining boundary pipes between DMAs. Then, the nondominated sorting genetic algorithm III (NSGAIII) method is employed to select the optimal arrangement of valves and flowmeters on boundary pipes from multiple perspectives, controlling the opening and closing of valves to achieve dynamic DMA partition. In the case of L-TOWN, the results show that the employed method reduces the average pressure variance by 15.6% compared with Louvain algorithms in the optimal multilevel DMA, which also effectively reduces bad connections between DMAs. Additionally, the obtained dynamic DMA layout exhibits excellent hydraulic performance. Under the two abnormal conditions, including fire events and increased water demand, the resilience index increased by 42% and 16%, respectively. [ABSTRACT FROM AUTHOR]

Although pressure regulation valves (PRVs) are commonly used for reducing leakage in water distribution networks (WDNs), in recent years, many studies have highlighted the opportunity of using pumps as turbines (PATs) so as to couple pressure reduction (and thus leakage reduction) with hydropower generation. Unlike in water transmission systems however, flow discharge in a WDN varies continuously, consequently requiring real-time control (RTC) of pressure. Nevertheless, RTC of a PAT in a WDN remains an open issue, due to the lack of information and knowledge about PAT operation in a real environment. Whereas previous experimental studies have described PAT installation with a frequency converter in which the power produced gets dissipated through electrical resistance, in the hydraulic regulation layout, impeller speed depends on the electrical grid. Consequently, this paper proposes a comprehensive algorithm to both control the pressure at the control node of a WDN and produce power through a PAT directly connected to the electrical grid. The operation of the prototype was considered under hydraulic regulation, demonstrated by several studies to represent the most effective trade-off between costs and benefits. Further testing by means of laboratory experiments designed to simulate the operation of a grid-connected PAT installed in a WDN effectively validated the robustness of the proposed method. The results proved the ability of the prototype and algorithm to couple hydropower generation with pressure control even when the flow varied suddenly. [ABSTRACT FROM AUTHOR]

In this paper, a model with integration of interval programming (IP), chance-constrained programming (CCP), and fuzzy random variables (FRVs), termed as an inexact fuzzy random chance-constrained programming (IFRCCP) model, was proposed to deal with the fuzzy and random uncertainties in optimization of booster cost for a water distribution system (WDS) under uncertainty. The IFRCCP model was applied to a WDS to verify the efficiency of the method. After formulating the IFRCCP model, the booster cost intervals were obtained under various violation levels and confidence levels. The results indicated that the lower and upper booster costs increased with the confidence levels of the lower limits, and decreased with the violation levels of the lower limits. Moreover, the nodal chlorine concentrations are more uniform with the increase of booster numbers. The booster costs under trapezoidal distribution FRVs are greater than that under triangular distribution FRVs. Moreover, the uniformity of nodal chlorine concentration under triangular fuzzy distributions is larger than that under trapezoidal fuzzy distributions. The results obtained can help managers to make schemes on booster optimization under fuzzy and random uncertainties. [ABSTRACT FROM AUTHOR]

Polymeric fibers are often used as a drying additive for refractory castables because they can increase their permeability, reducing the risk of pressurization that is believed to trigger explosive spalling. Despite the potential of synthetic polymers to be engineered and obtain desired properties, the required parameters for inducing permeability enhancement remain unclear. This inhibits the development of novel designed drying additives and improvement of the numerical models. This work investigates the effect of polypropylene (PP), polyethylene (PE) and cellulose fibers on the water transport in refractory castables through rapid neutron tomography, enabling the in situ visualization of the water distribution, the drying front advance and the size, intensity and duration of moisture accumulation. PE and cellulose fibers accelerate drying fronts earlier than PP, in which PE exhibits larger moisture accumulation, residual moisture behind its drying front and a slower drying rate at higher temperatures despite the early water removal initiation. In contrast, cellulose emerged as a better candidate, due to a swelling–shrinkage based mechanism. The neutron tomography observations unveil the dynamic and intricate effect of fibers in the permeability, emphasizing that safer industrial processes require a deeper understanding of the underlying mechanisms to develop better fibers and accurate numerical models. [ABSTRACT FROM AUTHOR]

Copyright of Tecnología y Ciencias del Agua is the property of Instituto Mexicano de Tecnologia del Agua (IMTA) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article discusses a project in Italy that addressed the issue of hexavalent chromium (Cr(VI)) in groundwater in the province of Piacenza. Due to new regulations, an iterative process was developed to assess the problem, identify treatment technologies, define project priorities, and implement solutions within budget and time constraints. The project included site identification, technology choices, intervention planning, and process improvements, resulting in improved water quality and reduced Cr(VI) levels ahead of regulatory deadlines. The project showcased efficient planning and technology selection for successful implementation. [Extracted from the article]

Mining causes damage to the soil and rock mass, while rainfall has a pivotal impact on the mining slope stability, even leading to geological hazards such as landslides. Therefore, the study evaluated the mine landslide stability and determined the effectiveness of the treatment measures under the impact of pore water pressure changes caused by rainfall, taking the Kong Mountain landslide in Nanjing, Jiangsu Province, China, as the research object. The geological conditions and deformation characteristics were clarified, and the failure mechanism and influencing factors were analyzed. Also, the landslide stability was comprehensively evaluated and calculated utilizing the finite element-improved limit equilibrium method and FLAC 3D 6.0, which simulated the distribution of pore water pressure, displacement, etc., to analyze the influence of rainfall conditions and reinforcement effects. The results indicated the following: (1) Rainfall is the key influencing factor of the landslide stability, which caused the pore water pressure changes and the loosening of the soil due to the strong permeability; (2) The distribution of the pore water pressure and plastic zone showed that, during the rainfall process, a large area of transient saturation zone appeared at the leading edge, affecting the stability of the whole landslide and led to the further deformation; (3) After the application of treatment measures (anti-sliding piles and anchor cables), the landslide stability increased under both natural and rainfall conditions (from 1.02 and 0.94 to 1.38 and 1.31, respectively), along with a reduction in displacement, plastic zones, etc. The Kong Mountain landslide, with the implemented treatment measures, is in good stability, which is in line with the evaluation and calculation results. The study provides certain contributions to the stability evaluation and treatment selection of similar engineering under rainfall infiltration. [ABSTRACT FROM AUTHOR]

Some water distribution pipe networks were constructed several decades ago and have been damaged. The old pipe network has experienced many leaks and should be rehabilitated. In old cities like Jakarta, with high leak rates (1.6 leaks/km/year), pipeline network managers must frequently repair leaks or perform reactive maintenance. Far too many pipes need to be rehabilitated compared to the available budget. This research will develop an optimization model for selecting rehabilitated pipes under reactive maintenance conditions, which has never been performed before. The selection of pipe segments to be rehabilitated must be optimal to obtain maximum benefits using minimum costs. The variables that influence rehabilitation costs and benefits and the relationship between these variables need to be known to optimize the selection. The influencing variables and their model structure were obtained from literature reviews and surveys of respondents with sufficient experience in water pipe network management. These influential variables have varying characteristics. Data processing and analysis uses the confirmatory factor analysis (CFA) method with a formative–formative measurement model. In total, 22 variables were found to be valid and significantly influenced the cost and benefits of rehabilitation. The analysis results are a structural model of the relationship between variables that influence the costs and benefits of rehabilitation in reactive maintenance with a limited budget, which can be used to optimize rehabilitation models. [ABSTRACT FROM AUTHOR]

Managing water supply systems is essential for developing countries to face climate variability in dryland settings. This is exacerbated by high energy costs for pumping, water losses due to aging infrastructures, and increasing demand driven by population growth. Therefore, optimizing the available resources using a water–energy nexus approach can increase the reliability of the water distribution network by saving energy for distributing the same water. This study proposes a methodology that optimizes the Water Distribution Network (WDN) and its management that can be replicated elsewhere, as it is developed in a data-scarce area. Indeed, this approach shows the gathering of WDN information and a model to save energy by optimizing pump schedules, which guarantee water distribution at minimal operational costs. The approach integrates a genetic algorithm to create pumping patterns and the EPANET hydraulic simulator to test their reliability. The methodology is applied for a water utility in the dryland urban setting of Lodwar, Turkana County, Kenya. The results indicate a potential reduction in energy costs by 50% to 57% without compromising the supply reliability. The findings highlight the potential of WEN-based solutions in enhancing the efficiency and sustainability of data-scarce water utilities in dryland ecosystems. [ABSTRACT FROM AUTHOR]

Rapid population growth and subsequent urbanization pose significant challenges of water shortage in arid regions. As an important area along the One Belt and One Road line, the Northern Slope of Tianshan Mountains (NSTM) has suffered from water shortages owing to rapid urbanization in recent decades. To conserve water resources and protect the ecosystem, understanding the temporal and spatial variations of the domestic water consumption, availability, and its influencing factors is essential. According to water resource regionalization and its characteristics in NSTM, it was divided into three sections, namely the west section, the middle section, and the east section. In addition, this work characterized the temporal and spatial variation of domestic water consumption in NSTM with a focus on the understanding of the influence of urbanization on domestic water consumption from 1990 to 2020 based on three sections. The results showed that during this period of time, construction land use increased by 2256 km2 corresponding to the population increase of 158.58 × 104. Subsequently, the total domestic water consumption increased from 7.55 × 107 m3 in 1990 to 2.60 × 108 m3 in 2020. The eastern section demonstrated steady growth, while the western and middle sections experienced larger fluctuations in domestic water consumption. Urbanization has been identified as a significant factor influencing the shift in domestic water consumption. This study offers a scientific foundation for the sustainable management of water resources in arid areas. [ABSTRACT FROM AUTHOR]

Predicting essential water quality parameters, such as discharge, pressure, turbidity, temperature, conductivity, residual chlorine, and pH, is crucial for ensuring the safety and efficiency of water supply systems. This study employs long short-term memory (LSTM) networks to address the challenge of capturing temporal dependencies in these complex processes. Our approach, using a robust LSTM-based model, has demonstrated significant predictive accuracy, as evidenced by substantial R-squared values (e.g., 0.86 for discharge and 0.97 for conductivity). These models have proven particularly effective in handling non-linear patterns and time-series data, which are prevalent in water quality metrics. The results indicate the potential for LSTMs not only to enhance the real-time monitoring of water systems but also to aid in the strategic planning and management of water supply systems. This study's findings can serve as a basis for further research into the integration of AI in environmental engineering, particularly for predictive tasks in complex, dynamic systems. [ABSTRACT FROM AUTHOR]

This study investigated the impact of gradient milling on the cooking properties and sensory characteristics of Yangxian black rice. The results showed that as the degree of milling increased, the gelatinization time decreased (36.85–23.54 min) and the water uptake ratio of whole black rice (188.29%) was significantly lower compared to that of refined grains (194.05%). Low-field nuclear magnetic resonance (NMR) was further used to monitor the water concentration and distribution of black rice during soaking and cooking. It was found that the bran layers of black rice, as a physical barrier, impeded the water penetration into the kernels for a given soaking and cooking duration. The sensory evaluation conducted by a panel of trained volunteers demonstrated a high score for all sensory attributes in slightly milled black rice, corroborating findings from the taste analyzer. Through correlation analysis of volatile components determined by gas chromatography-mass spectrometry (GC-MS), smell scores in sensory evaluation, and electronic nose response values, 2-pentyl-furan (54.84–12.72 ng/g) and guaiacol (19.39–5.51 ng/g) were found to be the predominant volatile flavor contributors in cooked black rice. Overall, this study provides valuable insight into the intricate relationship between milling degrees and the cooking properties, sensory characteristics, and volatile flavor compounds of Yangxian black rice. [ABSTRACT FROM AUTHOR]

In many processes and applications, the performance of textiles relies heavily on fluid transport; for example, the in-plane distribution of water and the through-plane permeation of water vapor and air. Prediction of knitted fabrics' effective transport characteristics can enhance development workflows and bring them to new applications. Effective transport parameters that are particularly important are the permeability and diffusive mass transfer. Usually, experiments are used to determine these parameters. It is desirable to conduct a thorough investigation into how yarn structure and knitting gauge influence these properties to tailor knitted fabrics for a particular application. Our contribution in this context describes a consistent workflow to forecast the effective mass transfer characteristics of single jersey fabrics. Single jersey fabrics have been chosen for they are the simplest patterning, and are widely used in body-near worn garments. The proposed approach involves visualizing fabric samples with a light microscope, and subsequently determining relevant geometric parameters through automated image processing algorithms. With these parameters in hand, a representative elementary volume of the fabric is constructed. The yarn is modeled as an effective medium to reduce calculation time. The representative elementary volume is then used for numerical predictions of air permeability and the diffusive water vapor transport. The predicted through-plane gas transport properties are compared with experimental data to validate the approach. Six different single jersey polyester fabrics were analyzed, with different yarn structures and machine gauges. The comparison shows a good agreement between simulated and measured transport properties. [ABSTRACT FROM AUTHOR]

Karst landscape, characterised by drought-prone areas, limited water retention and nutrient-poor soils, pose significant challenges for the sustainability of small-scale agricultural systems. This study investigated the impact of smart precision irrigation (SPI) technology, which integrates drip irrigation (DI) and organic fertilisation, on the growth, physiological performance and water use efficiency of chilli plants cultivated in a karst landscape in Gunungkidul District, Yogyakarta, Indonesia. This experiment involved a combination of drip irrigation (D), non-drip irrigation (ND), organic fertiliser (F), and no fertiliser (NF), with a semi-automatically installed SPI system to monitor and adjust soil moisture and watering requirements. The results showed that the combination of drip irrigation and organic fertiliser (D + F) significantly increased plant growth parameters, including plant height, leaf area, and chlorophyll content, and improved physiological traits such as photosynthetic rate, stomatal conductance, and leaf water use efficiency (LWUE). These improvements were attributed to the optimised water distribution and nutrient availability provided by the DI system, which minimised water loss and reduced drought stress, as evidenced by lower proline accumulation and reduced antioxidant enzyme activity in plants. In addition, the D+F treatment resulted in the highest biomass production, fruit yield and water use efficiency, underlining its potential as a sustainable agricultural practice in waterscarce karst environments. The study concludes that adopting organic matter irrigation and fertilisation strategies can improve the productivity and resilience of horticultural crops in areas facing similar environmental constraints. [ABSTRACT FROM AUTHOR]

Ground deformation induced by frost heave is a matter of concern in cold region engineering construction since it affects surrounding structures. Frost heave, which is related to the heat-water-stress interaction, is a complicated process. In this study, a heat-water-stress coupling model was established for saturated frozen soil under different stress levels to quantify the water redistribution, heat transfer, frost heave, and water intake. An empirical formula for the soil permeability considering the confining and deviator pressures was employed as an indispensable hydraulic equation in the coupling model. The Drucker-Prager yield criterion matched with the Mohr-Coulomb criterion was employed in the force equilibrium equation to investigate the deformation due to the deviator and confining pressures. The anisotropic frost heave during unidirectional freezing was further considered in the coupling model by introducing an anisotropic coefficient. Subsequently, based on the above coupling relationship, a mathematical module in COMSOL Multiphysics was applied to calculate the governing equation numerically. Finally, the proposed model was validated through an existing frost heave experiment conducted under various temperature gradients and stress levels. The results of the freezing front, water redistribution, water intake, and frost heave ratio predicted using the proposed model were found to be consistent with the experimental results. [ABSTRACT FROM AUTHOR]

Numerous studies have demonstrated that high suspended sediment concentration (SSC) can change density distribution and affect water mixing, but few scholars have investigated this impact on numerical simulations of estuarian salinity distribution. The Qiantang Estuary is a macro-tidal estuary with high SSC, which has a more significant influence on water density than that of salinity. Therefore, this paper established a three-dimensional (3D) numerical model coupling flow, salinity and SSC based on Delft3D and first analyzes the impact of SSC on salinity distribution under different runoff and tidal conditions in the Qiantang Estuary. The results indicated that simulated salinity generally decreases when considering the impact of SSC, suggesting a weakening effect on saltwater intrusion. The distribution of salinity difference (DS) and SSC show a strong spatial and temporal correlation, and DS peak increases and shifts upstream as the tidal range increases or runoff discharge decreases. The mechanism of SSC influencing saltwater intrusion can be summarized as follows: On the one hand, SSC increases the water density, which weakens the driving force for saltwater to move upstream, causing a decrease in flood current velocity and water level, and thereby diminishing the advective transport of salinity. On the other hand, SSC enhances density stratification, which weakens vertical turbulence and reduces the dispersive transport of salinity. These combined effects reduce both the advective and diffusive salinity fluxes during the flood tide, ultimately leading to a decrease in upstream salinity. Therefore, neglecting this effect in estuaries with high SSC can cause significant deviations in salinity simulation results, especially under low-flow and high-tide conditions. [ABSTRACT FROM AUTHOR]

The optimal design of water distribution networks (WDNs) has always attracted the attention of researchers due to the complexities involved. The general cost optimization problem is categorized as the NLP-Hard problem. Several evolutionary algorithms (EAs) that can explore the entire search from multiple starting points have been developed in the last three decades. The EAs have more chances of reaching the global optimal solution. However, whether these algorithms converge to a global optimal solution or not is always doubtful, as these algorithms do not guarantee the same solution in the two different runs. A two-source benchmark network is considered for which several better solutions have been reported by different researchers in the last 15 years. The available solutions of this network are analysed based on certain parameters, usually observed in the global optimal solution. The main objective of the study is to explore the possibility of achieving a better than the current best-solution, as the global optimality of the current best is not confirmed. Further, the proposed methodology is applied to test the current best solutions of two additional networks. [ABSTRACT FROM AUTHOR]

AbstractAsbestos is a group of naturally occurring fibrous minerals that were commonly used in the construction of cement pipes for drinking water distribution systems. These pipes deteriorate and can release asbestos fibers into drinking water, raising concerns about potential risk to human health. The objective of this work was to synthesize human, animal, and in vitro evidence on potential health risks due to ingested asbestos in drinking water and evaluate the weight of evidence (WoE) of human health risk. A systematic review of epidemiological evidence was conducted, along with critical review of animal and in vitro evidence, followed by WoE evaluation that integrated human, animal, and in vitro evidence. The systematic review included 17 human studies with health outcomes mostly related to various cancer sites, with the majority focusing on the gastrointestinal system. The WoE evaluation resulted in very low levels of confidence or insufficient evidence of a health effect for cancers in 15 organ systems and for three non-cancer endpoints. While eight studies reported possible associations with stomach cancer in males, few high-quality studies were available to verify a causal relationship. Based on high-quality animal studies, an increased risk for cancer or non-cancer endpoints was not supported, aligning with findings from human studies. Overall, the currently available body of evidence is insufficient to establish a clear link between asbestos contamination in drinking water and adverse health effects. Due to the lack of both high-quality epidemiological studies and a validated kinetic model for ingested asbestos, additional research on this association is warranted. [ABSTRACT FROM AUTHOR]

An accurate estimation of leakages in water distribution networks is of primary importance for the definition of strategies aimed at ensuring an efficient management of water resources and avoiding water waste. However, in the case of methods based on water balance—such as the Minimum Night Flow method—inaccurate assessment of the minimum night consumption (MNC), e.g. the assumption of fixed MNC values from the literature, can heavily mislead the quantification of leakage level. This study aims at providing insights into the variability of MNC and the related drivers. In greater detail, hourly water consumption data of approximately 200 users are collected over a period of two years and subjected to a multi-phase methodology to obtain a detailed characterization of MNC, with and without considering the users affected by post-meter leakages. The study demonstrates that factors such as seasonality or the presence of post-meter leakages may strongly impact the MNC—the values of which can significantly deviate from the literature references—and thus lead to significant misestimation of network leakages in water systems. Highlights: A methodology for the statistical analysis of minimum night consumption (MNC) based on the daily water-consumption profiles at the user level is proposed. The methodology is applied to hourly-resolution water-consumption data collected over two years in a sample of over 200 users. Occupancy rate, seasonality, and presence of post-meter leakages affect MNC statistics. [ABSTRACT FROM AUTHOR]

In the derection of remote sensing (RS) image analysis, semantic segmentation, as an important technology, is of key significance for the identification and analysis of land surface cover types. In recent years, applying deep learning models to tasks such as road extraction, water distribution extraction, building classification and building segmentation from RS images has become an important research hotspot. Due to its limited receptive field, traditional convolutional neural networks (CNN) cannot effectively capture global context information. Transformer uses the multi-head self-attention mechanism to capture a wide range of information and can solve this problem well. Therefore, we proposed ST-MDAMNet based on Swin Transformer and combined with the multi-dimensional attention mechanism. First, a feature enhancement module (FAM) is introduced after each stage of the Swin Transformer encoder to effectively enhance the model's proficiency in identifying essential information. Secondly, a feature fusion module (FFM) is proposed to effectively fuse the multi-scale information of the encoder part. It further improves the expression ability of different dimensional features and effectively improves the detection effect of small targets. Ultimately, the fused features are input into the multi-dimensional attention module (MDAM) to carefully optimize the features, which greatly increases the effect of semantic segmentation of RS images. We demonstrate the effectiveness of each module through ablation experiments. Comparative experiments are completed on two publicly large-scale datasets, and the proposed method shows excellent results compared with state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Two pedotransfer functions (PTFs) are available in the literature enabling the soil water retention function (WRF) to be estimated from knowledge of the soil particle-size distribution (PSD), oven-dry soil bulk density (rb), and saturated soil water content (qs): i) the Arya and Heitman model (PTF-AH), and ii) the Mohammadi and Vanclooster model (PTF-MV). These physicoempirical PTFs rely on the hypothesis of shape similarity between PSD and WRF, and do not require the calibration of the input parameters. In the first stage, twenty-seven PSD models were evaluated using 4,128 soil samples collected in Campania (southern Italy). These models were ranked according to the root mean square residuals (RMSR), corrected Akaike information criterion (AICc), and adjusted coefficient of determination (R2adj). In the second stage, three subsets of PSD and WRF data (DS-1, DS-2, and DS-3), comprising 282 soil samples, were used to evaluate the two PTFs using the best three PSD models selected in the first stage. The hypothesis of shape similarity was assumed as acceptable only when the RMSR value was lower than the field standard deviation of the WRFs (s*), which is viewed as a tolerance threshold and computed from the physically based scaling approach proposed by Kosugi and Hopmans (1998). In the first study area (DS- 1), characterized by a fairly uniform, loamy textured volcanic soil, the PTF-AH outperformed the PTF-MV and both PTFs provided reasonable performance within the acceptance threshold (i.e., RMSR < s*). In the other two heterogeneous field sites (DS-2 and DS-3, characterized by soil textural classes that span from clay and clay-loam to loam and even sandy-loam soils), the PTF-MV (with 3% to 6% RMSR surpassing s*) outperformed the PTF-AH (with 8% to 30% RMSR surpassing s*) and the majority of RMSR values were larger than those obtained in the original studies. The mean relative error (MRE) revealed that the PTF-MV systematically underestimates the measured WRFs, whereas the PTF-AH provided negative MRE values indicating an overall overestimation. The outcomes of our study provide a critical evaluation when using calibration-free PTFs to predict WRFs over large areas [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive review of the methods and techniques developed for detecting leaks in water distribution systems, with a focus on highlighting their strengths, weaknesses, and areas for future research. Given the substantial economic, social, and environmental impacts of undetected leaks, timely detection and precise location of leaks are critical concerns for water authorities. This review categorizes existing methods into traditional approaches, such as manual sounding, and modern techniques involving smart water management and sensor technologies. A multidimensional bibliometric analysis was employed to systematically identify, select, and evaluate 600 scholarly articles on water leak detection, sourced from the Scopus database over a 23-year period (2000–2023). The paper evaluates each method based on leak sensitivity, burst detection, continuous monitoring, alarm accuracy, and implementation costs. Novel insights include an analysis of emerging smart water technologies and their integration into real-world water distribution networks, offering improved efficiency in leak detection. The paper also identifies key gaps in current research and suggests future directions for advancing the accuracy and cost-effectiveness of these technologies. [ABSTRACT FROM AUTHOR]

The penetration rate of water supply via water supply facilities in the Republic of Korea has reached 99%, with 94% of the energy for operation consumed by pumps transporting water. Consequently, developing efficient pump operation techniques is crucial for reducing energy costs in water supply systems. This study employs real-coded genetic algorithm techniques to compute optimized demand patterns, considering the utilization of water tanks within networks. Hydraulic appropriateness is verified by evaluating pressure within nodes determined by derived patterns through numerical analysis simulations. Furthermore, after calculating flows supplied to the networks, pump power is determined, and resultant energy costs are estimated to evaluate economic feasibility. Results indicate that pressure distribution in networks with optimal patterns is hydraulically appropriate, meeting hydrodynamic pressure conditions suggested in water supply design standards. Additionally, this study demonstrates a 9% reduction in network energy costs compared to existing patterns. The model presented herein offers a means to efficiently operate water supply systems through water tanks, thereby reducing energy costs. [ABSTRACT FROM AUTHOR]

Drinking water distribution systems (DWDSs) may be contaminated to various degrees when different microorganisms attach to the pipe walls. Understanding the characteristics of biofilms on pipe walls can help prevent and control microbial contamination in DWDSs. The biofilm formation, interspecific interactions, and chlorine resistance of 10 dual-species biofilms in polyethylene (PE) and cast iron (CI) pipes were investigated in this paper. The biofilm biomass (heterotrophic bacterial plate count and crystal violet) of dual species in CI pipes is significantly higher than that in PE pipes, but the biofilm activity in CI pipes is significantly lower than that in PE pipes. The interspecific interaction of Sphingomonas-containing group presented synergistic or neutral relationship in PE pipes, whereas the interspecific interaction of the Acidovorax-containing group showed a competitive relationship in CI pipes. Although interspecific relationships may help bacteria resist chlorine, the chlorine resistance was more reliant on dual-species groups and pipe materials. In CI pipes, the Microbacterium containing biofilm groups showed better chlorine resistance, whereas in PE pipes, most biofilm groups with Bacillus exhibited better chlorine resistance. The biofilm groups with more extracellular polymeric substance (EPS) secretion showed stronger chlorine resistance. The biofilm in the PE pipe is mainly protected by EPS, while both EPS and corrosion products shield the biofilms within CI pipe. These results supported that dual-species biofilms are affected by pipe materials and interspecific interactions and provided some ideas for microbial control in two typical pipe materials. [ABSTRACT FROM AUTHOR]

Considerable amounts of irrigation water of vegetable crops grown in homogenous sandy soil profiles could be subjected to deep percolation water losses due to inappropriately designed surface or subsurface drip irrigation methods. This study aimed to investigate the combined influence of implementing clay soil layer in homogenous sandy soil profile of low-tech greenhouse ridges and using modified surface drip irrigation (M-DI) on soil moisture distribution and water productivity of tomatoes. In the greenhouse, a 7.5 cm thick clay soil layer was implemented 15 cm from the soil surface of each ridge as a hydraulic barrier. Three irrigation regimes (100%, 70% and 50% of ETo) were imposed with the M-DI on tomato plants and 100%ETo with surface drip irrigation (DI) as control. Regarding economic valuation, viability was preserved for the M-DI and DI methods. The outcome indicated that soil moisture spreads more horizontally than vertically on the sandy soil above the clay soil layer. The combined effect of the homogenous sandy soil profile amendment and full irrigation (100%ETo) with the M-DI irrigation method increased the tomato fruit yield by 64.5%. Furthermore, the combined influence enhanced water productivity by the M-DI to 54.7 kg/m3 compared to 32 kg/m3 by the DI. However, M-DI demonstrated dominance over DI regarding returns, yield, and profit. Economic-wise, the M-DI requires 50% less of the lateral pipelines needed by the DI in low-tech greenhouses. Adopting the M-DI with a hydraulic barrier can improve soil moisture, water productivity, yield, and returns for tomato crops in low-tech greenhouses under sandy soil conditions. Also, the M-DI with the hydraulic clay barriers was an economically viable investment compared to the DI without clay barriers for growing tomatoes in low-tech greenhouses. [ABSTRACT FROM AUTHOR]

Copyright of Food & Fermentation Industries is the property of Food & Fermentation Industries and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Science & Technology of Food Industry is the property of Science & Technology of Food Industry Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)